Objective: To construct Markov model for clinical follow up data and predict the number of survivals and deaths. Methods: The state of patients was classified into survival. death and censorship. The weighted least sq...Objective: To construct Markov model for clinical follow up data and predict the number of survivals and deaths. Methods: The state of patients was classified into survival. death and censorship. The weighted least squares method was used for estimating parameters. Results: Markov model for survival analysis of follow--up data was presented. By using an example, the transition probability matrices were obtained and the number of survivals and deaths at each observation point was predicted respectively. Conclusion: Markov model constructed in the present study to analyze clinical follow up data could be used as effective supplemention for life table analysis.展开更多
文摘Objective: To construct Markov model for clinical follow up data and predict the number of survivals and deaths. Methods: The state of patients was classified into survival. death and censorship. The weighted least squares method was used for estimating parameters. Results: Markov model for survival analysis of follow--up data was presented. By using an example, the transition probability matrices were obtained and the number of survivals and deaths at each observation point was predicted respectively. Conclusion: Markov model constructed in the present study to analyze clinical follow up data could be used as effective supplemention for life table analysis.
